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ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information Technology Institute of Applied Computer Systems Department of Systems Theory and Design E-mail: Janis.Grundspenkis@rtu.lv THE ROLE OF FIRST ORDER LOGIC IN ARTIFICIAL INTELLIGENCE

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The Role of First-Order Logic In Artificial Intelligence Logic is the oldest form of knowledge representation in a computer. Logic concentrates on using knowledge in a rigorous, provably correct way. Logic representation techniques linked with intelligent systems offer a formal well- founded approach to knowledge representation and reasoning.

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The Role of First-Order Logic In Artificial Intelligence Logical formalism suggests a powerful way of deriving new knowledge from old – mathematical deduction. In this formalism conclusion can be made that a new statement is true by proving that it follows from the statements that are already known. First-order logic have sound and complete formal inference rules.

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The Role of First-Order Logic In Artificial Intelligence Logic as a formal system lends itself to automation. A wide variety of problems can be attacked by representing the problem description and relevant background information as logical axioms and treating problem instances as theorems to be proved.

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The Role of First-Order Logic In Artificial Intelligence Logical knowledge representation approach forms the basis upon which most Artificial Intelligence programming languages (PROLOG, for example) and shells are built.

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The Role of First-Order Logic In Artificial Intelligence Artificial Intelligence programming requires means of capturing and reasoning about qualitative aspects of a problem. First-Order Logic directly captures the descriptive knowledge.

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The Role of First-Order Logic In Artificial Intelligence First-Order Logic provides artificial intelligence programmers with a well- defined language for describing and reasoning about qualitative aspects of a system. First-Order Logic is sufficiently general to provide a foundation for other formal models of knowledge representation.

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The Role of First-Order Logic In Artificial Intelligence Logic is not suitable for all problems. Some knowledge resists embodiment in axioms. Logic is weak as a representation for certain kinds of knowledge.

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The Role of First-Order Logic In Artificial Intelligence The notation of pure logic does not allow to express such notations as heuristic distances (state differences). It is difficult to develop a system that could consistently solve complicated problems.

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The Role of First-Order Logic In Artificial Intelligence This is due to the fact that complex logical systems are able to generate an infinite number of provable theorems: without powerful techniques (heuristics) to guide their search, which is inherently exponential, automated theorem provers proved large number of irrelevant theorems.

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The Role of First-Order Logic In Artificial Intelligence Consequently, theorem provers may not help to solve all hard practical problems, even if they do their work instantaneously.

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First-Order Logic This is one of the most common and widely studied knowledge representation languages. Propositional Logic – limited to facts. First Order Logic (Predicate Logic) – world has objects (things with individual identities).

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First-Order Logic Properties (for example, red, round, prime, multi-stored) to distinguish different objects (for example, houses, names, colors, sizes, numbers, theories, basketball games, centuries). Relations among objects (for example, larger, smaller, inside, part of, has color, owns, father of, best friend, one more than).

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First-Order Logic Some relations are Functions (only one value results from one input), for example father of, one more than, etc. Facts than are objects, properties, or relations.

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